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INDONESIA
Jurnal Sains dan Teknologi
Published by CV ITTC Indonesia
ISSN : -     EISSN : 28077393     DOI : 10.47233
Core Subject : Science, Education, Engineering,
Aerospace Engineering Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Electrical & Electronics Engineering Energy Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mathematics Mechanical Engineering
Jurnal Sains Dan Teknologi (JSIT), merupakan Jurnal Penelitian dan Kajian Ilmiah yang diterbitkan CV.ITTC - INDONESIA dan dikelola langsung oleh Webinar.Gratis dan Even.Gratis yang terbit 3 (tiga) kali dalam setahun. Penyunting menerima kiriman naskah hasil kajian dan penelitian untuk bidang, Teknik Elektro, Teknik Sipil, Teknik Mesin, ,Teknologi Informasi.
Arjuna Subject : Umum - Umum
Articles 218 Documents
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A Implementasi K-Means Clustering dalam Segmentasi Citra Hewan pada Kucing, Kambing, dan Burung Delvi, Syerlin Aprilia; Ramadhanu, Agung
Jurnal Sains dan Teknologi (JSIT) Vol. 5 No. 3 (2025): September-Desember
Publisher : CV. Information Technology Training Center - Indonesia (ITTC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jsit.v5i3.3632

Abstract

Image segmentation is one of the most important challenges in digital image processing because it determines the successof separating the main object from the background so that visual information can be further analyzed. The problem ariseswhen the object has complex color, texture, and shape characteristics, as in animal images that often have color patternssimilar to their surroundings, making object boundaries difficult to distinguish clearly. This study aims to apply the KMeans Clustering method in the process of animal image segmentation—specifically for cats, goats, and birds—and toevaluate its effectiveness in identifying and separating the main object from the background. The method used is the KMeans Clustering algorithm, an unsupervised learning technique that groups image pixels based on color similarity in theRGB color space through an iterative process until centroid stability is achieved and clusters representing different imageregions are formed. The results show that the K-Means method can produce good segmentation performance for imageswith uniform lighting and simple backgrounds but experiences a decrease in accuracy when the object’s color is similar toits environment. Overall, this algorithm is effective, simple, and can serve as a foundation for developing automatedanimal image identification and classification systems
Penerapan K-Means Clustering untuk Klasifikasi Citra Aksesoris Ekstraksi Warna dan Tekstur GLCM Zubaidah, Rima Puti; Ramadhanu, Agung
Jurnal Sains dan Teknologi (JSIT) Vol. 5 No. 3 (2025): September-Desember
Publisher : CV. Information Technology Training Center - Indonesia (ITTC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jsit.v5i3.3633

Abstract

The main problem in accessory image recognition lies in the similarity of physical shapes among objects such as bracelets, necklaces, and earrings, which often causes difficulties in the automatic classification process. This study aims to develop an accessory image classification system capable of accurately grouping objects based on a combination of color and texture features using the K-Means Clustering algorithm. The method used includes several preprocessing stages such as resizing images to ensure uniform dimensions and normalizing pixel values to achieve consistent data scales. Color features were extracted using RGB and HSV histograms to represent color variations, while texture features were obtained through the Gray Level Co-occurrence Matrix (GLCM) method with four parameters: contrast, correlation, energy, and homogeneity. All extracted features were then combined and analyzed using the K-Means algorithm with k=3, corresponding to the number of accessory categories. The results show that combining color and texture features produces a more optimal cluster separation compared to using single-feature extraction. The K-Means algorithm successfully grouped accessory images according to their respective categories with high consistency. These findings have potential applications in digital catalog management systems and product recommendation systems on e-commerce platforms.
Penerapan K-Means Clustering Pada Pengolahan Citra Jam Digital, Analog dan Monograph dengan Matlab Dinantia, Triend; Ramadhanu, Agung
Jurnal Sains dan Teknologi (JSIT) Vol. 5 No. 3 (2025): September-Desember
Publisher : CV. Information Technology Training Center - Indonesia (ITTC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jsit.v5i3.3634

Abstract

Manual grouping of clock types is time-consuming and prone to errors, necessitating an automatic method to accuratelyclassify digital, analog, and chronograph clocks. This study aims to implement the K-Means Clustering method ingrouping clock types using image processing techniques with Matlab. The applied method involves image processing withcolor space conversion from RGB to LAB, texture feature extraction using Gray-Level Co-occurrence Matrix (GLCM),and grouping using K-Means Clustering algorithm. Analysis was performed by calculating silhouette coefficient andDavies-Bouldin Index to evaluate cluster quality. Results show three clusters formed: analog clocks, digital clocks, andchronograph clocks with 99% accuracy, where 30 out of 30 image data were correctly identified. K-Means Clusteringmethod is proven effective and accurate in determining clock categories.
Analisis Persepsi Pengguna Jalan terhadap Penerapan Sistem Satu Arah: Studi Kasus Jalan Nani Wartabone, Gorontalo Ahmad, Noor Fatmawanti; Abas, Mohamad Ilyas
Jurnal Sains dan Teknologi (JSIT) Vol. 5 No. 3 (2025): September-Desember
Publisher : CV. Information Technology Training Center - Indonesia (ITTC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jsit.v5i3.3640

Abstract

Traffic congestion in educational areas is a persistent issue in medium-sized Indonesian cities, including Gorontalo. JalanNani Wartabone, adjacent to Gorontalo State University, frequently experiences congestion due to student mobility,vehicle flow, pedestrians, and street vendors. To mitigate this, the city government introduced a one-way traffic system, yetits effectiveness from users’ perspectives has not been fully evaluated. This study examines road user perceptions acrossfive dimensions: comfort, safety, efficiency, accessibility, and satisfaction. Data were collected from 200 respondents(students, pedestrians, drivers, vendors) using questionnaires and analyzed with SPSS through descriptive statistics, crosstabulations, and correlation analysis, complemented by spatial heatmaps from geotagged feedback. Results revealsignificant group differences: students and pedestrians perceived positive effects in traffic order and walkability, whiledrivers and vendors reported reduced accessibility and longer travel times. The study contributes a user-centered,evidence-based framework for inclusive traffic policy in secondary cities
Pengembangan Sistem Kalender Kerja Berbasis Website untuk Meningkatkan Efisiensi Pengelolaan Jadwal pada Bps Kota Kendari Aqsan, La ode Pali; Ananda, Muh. Rezky; Wulandari, Suci; Aksara, LM Fid; ., Isnawaty
Jurnal Sains dan Teknologi (JSIT) Vol. 5 No. 3 (2025): September-Desember
Publisher : CV. Information Technology Training Center - Indonesia (ITTC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jsit.v5i3.3565

Abstract

The Central Statistics Agency (BPS) of Kendari City plays a crucial role in statistical data management to support decision-making. Despite operational activities, employee work schedules are still managed manually, leading to a number of challenges, including delays in information processing, scheduling conflicts, and a lack of transparency. The main focus of this research is the development of an online work calendar system to support the efficiency and effectiveness of operational schedule management at BPS Kendari City. This system provides features such as daily, weekly, and monthly scheduling, automatic task reminder notifications, and reports that management can use to monitor employee activities. The development method used is the Waterfall model. The system development process includes several main stages: needs identification, design, implementation, testing, and comprehensive evaluation. The trials conducted showed that this system successfully improved the efficiency of work schedule management. The test results showed that the system was able to improve schedule management efficiency, minimize time conflicts, and improve internal coordination between employees. With the implementation of this system, it is hoped that BPS Kendari City can improve organizational performance and contribute to the creation of a more modern and technology-integrated government system.
Implementasi Image Processing dengan Metode K-Means Clustering untuk Identifikasi Buah Berry: Blackberry, Gojiberry, dan Mulberry Agsera, Nilam; Ramadhanu, Agung
Jurnal Sains dan Teknologi (JSIT) Vol. 5 No. 3 (2025): September-Desember
Publisher : CV. Information Technology Training Center - Indonesia (ITTC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jsit.v5i3.3625

Abstract

Berries are known as "super fruits" because they are rich in nutrients and antioxidants. Despite their abundant health benefits and significant economic potential in Indonesia, classifying berries like blackberries, goji berries, and mulberries is often challenging due to their visual similarities. This challenge hinders the sorting process in the agricultural and trade industries. This research proposes an automated classification model based on image processing to identify these three types of berries this study aims to develop and test effectiveness of an automatic classification model using image processing to accurately differentiate between blackberry, goji berry, and mulberry, in order to address the difficulties of manual sorting in the industry. The study implements K-Means Clustering as the primary technique for image segmentation, aiming to accurately separate the fruit from its background. The workflow begins with collecting 30 images of each berry type, followed by a color space transformation from RGB to Lab to separate color and brightness components. After segmentation, shape and texture feature extraction is performed to obtain the unique characteristics of each fruit. The analysis results show that feature extraction successfully captured significant differences between the three fruits. Blackberries tend to be rounder (metric: 0.56934; eccentricity: 0.56594), whereas goji berries (metric: 0.15132; eccentricity: 0.92832) and mulberries (metric: 0.097072; eccentricity: 0.87125) are oblong. Texture analysis also shows that mulberries have the smoothest surface. These quantitative differences are key to distinguishing the three fruits. Overall, this method provides an effective and accurate identification solution that can be implemented in automated fruit sorting systems to improve the production quality and economic value of berries in Indonesia.
Rancang Bangun Aplikasi Ppdb Di Mts Riset Fathul Huda dengan Metode Rad Berbasis Web Fajar, Nugroho Gusti Bintang; Budiman, Saiful Nur; Febrinita, Filda
Jurnal Sains dan Teknologi (JSIT) Vol. 5 No. 3 (2025): September-Desember
Publisher : CV. Information Technology Training Center - Indonesia (ITTC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jsit.v5i3.3649

Abstract

The New Student Admissions (PPDB) process at MTs Riset Fathul Huda has been carried out manually, resulting in various obstacles such as time inefficiency, potential data input errors, and difficulties in managing prospective student files. To overcome these problems, this study aims to design and build a web-based PPDB application using the Rapid Application Development (RAD) method. The RAD method was chosen because it is iterative and fast, and actively involves users in every stage of system development. The resulting application has various main features, including online registration, document upload, payment verification, and data management by the committee. System testing was carried out comprehensively through Black Box Testing, White Box Testing, and User Acceptance Test (UAT). The Black Box test results showed a functional success rate of 96.55%, while the White Box results showed a Cyclomatic Complexity (V(G)) value of 141, all of which have been tested. In addition, the UAT results showed a very high level of user satisfaction, namely 96% from the admin side and 93.33% from the applicant side. Based on the evaluation results, it can be concluded that the developed web-based PPDB application is feasible, efficient, and well-received by users. It can also be an effective solution for digitizing student admissions at MTs Riset Fathul Huda
Korelasi Kedalaman terhadap Nilai Resistivitas dan Parameter Geoteknik (N-SPT dan Kohesi) pada Tanah Vulkanik dengan Analisis Regresi dan Klaster Ismiralda, Dinta Anindy; Pamungkas, Helmi Setia Ritma; Irianto, Singgih
Jurnal Sains dan Teknologi (JSIT) Vol. 5 No. 3 (2025): September-Desember
Publisher : CV. Information Technology Training Center - Indonesia (ITTC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jsit.v5i3.3667

Abstract

This study aims to analyze the relationship between depth, resistivity, and geotechnical parameters (SPT-N and cohesion) of volcanic soils on the Cisadane River slopes, South Bogor, using regression and cluster analysis. Methods included geoelectrical surveys with Schlumberger and Wenner–Schlumberger configurations, borehole drilling up to 26.5 m with SPT tests, and direct shear laboratory testing for cohesion values. Regression analysis indicated a significant positive relationship between depth and SPT-N (R² = 0.411; p < 0.05), while cohesion showed a positive but statistically insignificant trend, and resistivity exhibited a weak negative relationship with depth. Cluster analysis grouped the data into three categories: (1) shallow upper layer with high resistivity and low SPT values; (2) dominant middle layer consisting of saturated clayey soils with moderate parameters; and (3) dense to hard lower layer with high resistivity, high SPT values, and stronger cohesion. These results demonstrate that the integration of regression and cluster analysis effectively reveals the relationship between resistivity and the mechanical properties of volcanic soils, thus supporting geotechnical investigations and landslide hazard mitigation in the South Bogor area.
Implementasi Klasifikasi Gambar Daun Pepaya Dan Daun Sirih Menggunakan Metode Convolution Neural Network (CNN) Dalimunthe, Marini Octavia; M. Tambunan, Diswan Lanro; Siahaan, Herlina Veronika; Ilham, Muhammad Taufik; Manullange, Windy Patricia
Jurnal Sains dan Teknologi (JSIT) Vol. 5 No. 3 (2025): September-Desember
Publisher : CV. Information Technology Training Center - Indonesia (ITTC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jsit.v5i3.3685

Abstract

Image-based classification of herbal plant leaves plays a vital role in supporting agricultural digitization and rapidmedicinal plant identification. This study aims to develop and analyze a classification system for papaya (Carica papaya)and betel (Piper betle) leaves using a Convolutional Neural Network (CNN) and a hybrid CNN–Support Vector Machine(SVM) approach. The dataset, obtained from a public Kaggle repository, consisted of 1,000 images equally dividedbetween the two classes and was split into 90% for training and 10% for validation. Each image was resized to 150×150pixels and augmented to enrich data variability. The CNN model, trained for up to 30 epochs using the Adam optimizer,achieved a training accuracy of 99.82% and a validation accuracy of 47%, indicating overfitting caused by its 3,824,934parameters. In contrast, the CNN–SVM hybrid model—using CNN as a feature extractor and SVM as a classifier—achieved a validation accuracy of 89% with balanced precision and recall across both classes. These findings demonstratethat while CNN effectively captures visual features, integrating SVM enhances generalization on small datasets. Thisresearch contributes to the development of efficient, stable, and interpretable herbal plant classification systems based onneural networks
Systematic Literature Review (SLR): Perkembangan Penelitian E-Goverment di Indonsia dengan VOSviewer Wijaya, Muhamad Ilham; Sari, Dela Puspita; Jarti, Nanda
Jurnal Sains dan Teknologi (JSIT) Vol. 5 No. 3 (2025): September-Desember
Publisher : CV. Information Technology Training Center - Indonesia (ITTC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jsit.v5i3.3690

Abstract

This study aims to analyze the development of e-government research in Indonesia using a Systematic Literature Review (SLR) approach supported by bibliometric analysis using VOSviewer software. The review was conducted on scientific publications obtained from the Google Scholar database between 2020 and 2025. The results indicate that the topic of e-government is strongly linked to themes such as bureaucratic transformation, good governance, digital public services, and information technology literacy. Through network visualization and keyword density, it was found that e-government research in Indonesia has experienced a significant increase in line with the Electronic-Based Government System (SPBE) policy. Furthermore, the analysis results show positive trends in Indonesia's E-Government Development Index (EGDI) and Human Capital Index (HCI), reflecting advances in digital infrastructure, increased public literacy, and the effectiveness of public services. Overall, this study concludes that the implementation of e-government in Indonesia plays a crucial role in realizing transparent, efficient, and sustainable governance, as well as supporting the achievement of the Sustainable Development Goals (SDGs).

Page 17 of 22 | Total Record : 218

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